A Predictive Model of Ischemic Heart Disease in Middle-Aged and Older Women Using Data Mining Technique.

Abstract

This study was conducted to identify ischemic heart disease-related factors and vulnerable groups in Korean middle-aged and older women using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Among the 24,229 people who participated in the 2017-2019 survey, 7249 middle-aged women aged 40 and over were included in the final analysis. The data were analyzed using IBM SPSS and SAS Enterprise Miner by chi-squared analysis, logistic regression analysis, and decision tree analysis. The prevalence of ischemic heart disease in the study results was 2.77%, including those diagnosed with myocardial infarction or angina. The factors associated with ischemic heart disease in middle-aged and older women were identified as age, family history, hypertension, dyslipidemia, stroke, arthritis, and depression. The group most vulnerable to ischemic heart disease included women who had hypertension, a family history of ischemic heart disease, and were menopausal. Based on these results, effective management should be achieved by applying customized medical services and health management services for each relevant factor in consideration of the characteristics of the groups with potential risks. This study can be used as basic data that can be helpful in national policy decision making for the management of chronic diseases.